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Music and Audio Information Search System

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... information about musical Artists, Albums and Tracks together: from MusicBrainz to my ontology. ... owl:Class rdf:ID='Album' ... – PowerPoint PPT presentation

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Title: Music and Audio Information Search System


1
Music and Audio Information Search System
  • Kiavash Bahreini 055251

2
Outline
  • Introduction
  • Semantic Web
  • What is Ontology?
  • Domains and ranges
  • Ontology Languages (OWL)
  • Search on the Web
  • Object-oriented Modeling Paradigm
  • Adaptable Inference Capabilities
  • Background
  • The Music Ontology and OWL
  • Protégé
  • JBuilder 2006
  • Jena 2.3 Ontology API

3
Outline (cont)
  • RDQL
  • Java Server Pages
  • Algernon
  • Tomcat
  • Microsoft SQL Server
  • Music and Audio system use case, implementation
    and execution
  • Execution of program in Browser
  • Running queries in Algernon
  • Running queries in SQL Server 2005
  • Some source codes for classes in Music and Audio
    ontology
  • Comparison of Semantic Search and Regular Search
  • Conclusion
  • References

4
Introduction
  • Internet changed the music industry. At first,
    sharing systems like Napster allowed people to
    share any song they had on their computer with
    millions other people.
  • Communities like this ontology started to appear.
  • The Music Ontology is an attempt to link all the
    information about musical Artists, Albums and
    Tracks together from MusicBrainz to my ontology.

5
Introduction (Cont)
  • The goal is to express all relations between
    musical information to help people finding
    anything about music and musicians. It is based
    around the use of machine readable information
    provided by any web site or web service on the
    Web.

6
Semantic Web
  • Common framework
  • Allows data
  • Sharing
  • Reuse
  • Across domains
  • Application
  • Enterprise
  • Community boundaries
  • Based on Resource Description Framework (RDF)
  • XML for syntax
  • URIs for naming.

7
What is Ontology?
  • At the heart of all Semantic Web applications is
    the use of ontologies. A commonly agreed
    definition of an ontology is An ontology is an
    explicit and formal specification of a
    conceptualisation of a domain of interest.

8
Domains and ranges
9
Ontology Languages (OWL)
  • OWL Lite
  • OWL DL
  • OWL Full

10
Search on the Web
  • Seeking information on the Web is widely used and
    will become more important as the Web grows.
    Nowadays, search engines browse through the Web
    seeking given terms within web pages or text
    documents without using ontologies.
  • Traditional search engines such as Yahoo are
    based on full-text search. These search engines
    are seeking documents, which contain certain
    terms.

11
Object-oriented Modeling Paradigm
  • In the past decade the object-oriented paradigm
    has become prevalent for conceptual modeling.
  • Object-oriented models can easily be visualized,
    thus making understanding conceptual models much
    simpler. Hence, any successful ontology modeling
    approach should follow the object-oriented
    modeling paradigm.

12
Adaptable Inference Capabilities
  • Inference mechanisms for deduction of information
    not explicitly asserted is an important
    characteristic of ontology-based systems.
    However, systems with very general inference
    capabilities often do not take into account other
    needs, such as scalability and concurrency.
  • For example, in the RDFS and OWL ontology
    languages it is possible to make some classes the
    domain or the range of some property. This
    statement can be interpreted as an axiom saying
    that for any property instance in the ontology,
    the source and target instances can be inferred
    to be members of the domain and target concepts,
    respectively.

13
Background
  • The Music Ontology is an effort of ZitGist LLC.
    to express musical relationships between artists,
    albums and tracks.
  • I used OWL and to query that same information
    using the RDQL query language for RDF and OWL.
  • The Music Ontology is mainly influenced by the
    MusicBrainz community music metadatabase. Most of
    the properties of this ontology reflect the
    relationships described in that database. Most of
    the relationship descriptions written in this
    document have been taken on the MusicBrainz Wiki

14
The Music Ontology and OWL
  • The Music Ontology is an application of the
    Ontology Web Language (OWL) because the subject
    area I am describing music albums, artists,
    audio files, audio file formats, encoding audio
    files, genre, instrument, key, note, official,
    resource, rhythm etc has so many competing
    requirements.
  • By using OWL, the Music Ontology gains a powerful
    extensibility mechanism, allowing
    Music-Ontology-based descriptions to be mixed
    with claims made in any other OWL and RDF
    vocabulary

15
Protégé
  • Protégé is
  • an ontology editor
  • knowledge-base editor
  • an open-source, Java tool
  • provides extensible architecture to create
    customized knowledge-based applications.
  • Developed by Stanford University, USA

16
Music and Audio Ontology (Classes)
  • Provides information on
  • Album
  • Artist
  • AudioFile
  • AudioFileType
  • Encoding
  • Instrument
  • Key
  • Live
  • Note
  • Official
  • Resource
  • Rhythm
  • Signal
  • Soundtrack
  • Spokenword
  • Track
  • Type

17
Music and Audio Ontology (Data Type and Object
Properties)
  • Provides information on
  • arranged
  • covered
  • djmix_of
  • duration
  • image
  • linkto_wikipedia
  • medley_of
  • member_of
  • performed
  • similar_to
  • trackNum
  • translation_of

18
Music and Audio Ontology (General structure)
19
(No Transcript)
20
(No Transcript)
21
JBuilder 2006
  • The system is written in JBuilder 2006. JBuilder
    is and IDE (Integrated Development Tools) for
    developing new application, web etc software
    based on Java Language. All of the packages and
    classes for using OWL and running queries are
    imported into this IDE.

22
Jena 2.3 Ontology API
  • Jena 2.3 Ontology API is a Java framework for
    building Semantic Web applications. Use RDF
    models in your Java applications with the Jena
    Semantic Web Framework.

23
RDQL
  • RDQL is a query language for RDF in Jena models.
    The idea is to provide a data-oriented query
    model so that there is a more declarative
    approach to complement the fine-grained,
    procedural Jena API.
  • It is "data-oriented" in that it only queries the
    information held in the models there is no
    inference being done. Of course, the Jena model
    may be 'smart' in that it provides the impression
    that certain triples exist by creating them
    on-demand.

24
Java Server Pages
  • JavaServer Pages (JSP) technology allows web
    developers and designers to rapidly develop and
    easily maintain information-rich, dynamic web
    pages that leverage existing business systems. As
    part of the Java family, the JSP technology
    enables rapid development of web-based
    applications that are platform independent.
  • In theory, JavaServer Pages technology separates
    the user interface from content generation,
    enabling designers to change the overall page
    layout without altering the underlying dynamic
    content.

25
Algernon
  • Algernon is a rule-based inference system,
    implemented in Java and interfaced with Protégé
    and it is developed by Micheal Hewett. It allows
    executing queries within the Protégé GUI.
  • It performs forward and backward rule-based
    processing of knowledge bases, and efficiently
    stores and retrieves information in ontologies
    and knowledge bases. It has an ability to call
    external Java methods and an internal LISP
    subsystem.

26
Tomcat
  • Tomcat is the official reference implementation
    of the Java Servlet 2.2 and JavaServer Pages 1.1
    technologies. Developed under the Apache license
    in an open and participatory environment, it is
    intended to be a collaboration of the
    best-of-breed developers from around the world.
  • Tomcat is a servlet container and JavaServer
    Pages(tm) implementation. It may be used stand
    alone, or in conjunction with several popular web
    servers
  • Apache, version 1.3 or later
  • Microsoft Internet Information Server, version
    4.0 or later
  • Microsoft Personal Web Server, version 4.0 or
    later
  • Netscape Enterprise Server, version 3.0 or later

27
Microsoft SQL Server
  • Microsoft SQL Server 2005 is a database and data
    analysis platform for large-scale online
    transaction processing (OLTP), data warehousing,
    and e-commerce applications.
  • The Database Engine is the core service for
    storing, processing, and securing data. The
    Database Engine provides controlled access and
    rapid transaction processing to meet the
    requirements of the most demanding data consuming
    applications within your enterprise. The Database
    Engine also provides rich support for sustaining
    high availability.

28
Music and Audio system use case, implementation
and execution
29
Music and Audio system use case, implementation
and execution
  • Execution of program in Browser

30
Music and Audio system use case, implementation
and execution
  • Execution of program in Browser

31
Music and Audio system use case, implementation
and execution
  • Running queries in Algernon
  • 1) Find all artist names that their age45,
    nationality"Turkish", country "Turkey", and
    numberOfAlbums50

32
Music and Audio system use case, implementation
and execution
  • Running queries in Algernon
  • 2) Find all WebSites Address for artists

33
Music and Audio system use case, implementation
and execution
  • Running queries in Algernon
  • 3) Find all album names which are not
    linkto_wikipedia site

34
Music and Audio system use case, implementation
and execution
  • Running queries in SQL Server 2005
  • 1) Find all artist names that their age45,
    nationality"Turkish", country "Turkey", and
    numberOfAlbums50

35
Music and Audio system use case, implementation
and execution
  • Running queries in SQL Server 2005
  • 2) Find all WebSites Address for artists

36
Music and Audio system use case, implementation
and execution
  • Running queries in Algernon
  • 3) Find all album names which are not
    linkto_wikipedia site

37
Music and Audio system use case, implementation
and execution
  • Some source codes for classes in Music and Audio
    ontology

38
Comparison of Semantic Search and Regular Search
  • In relational database management systems
    (RDBMS), there is no class relationship. It means
    sub classes cannot inherit all properties from
    their super classes and also there is no
    instantiation.
  • Extra work will be required to define class
    relations and all properties separately.
  • In semantic databases there are domains and
    ranges which can apply for each property but in
    an RDBMS it is impossible.
  • There is no object property for these systems.
  • In relational database Vastly coding
    implementation for returning data is need.
  • There is no way for using and importing
    ontologies, and for returning objects data types.

39
Comparison of Semantic Search and Regular Search
  • By using OWL, the Music Ontology gains a powerful
    extensibility mechanism, allowing
    Music-Ontology-based descriptions to be mixed
    with claims made in any other OWL or RDF
    vocabularies. I can re-use other ontologies to
    describe different relationship between classes.
  • OWL provides the Music Ontology with a way to mix
    together different descriptive vocabularies in a
    consistent way. Vocabularies can be created by
    different communities and groups as appropriate
    and mixed together as required, without needing
    any centralized agreement.
  • On the other hand, many existing SW tools are
    still file-oriented and also mine. This limits
    the size of ontologies that can be processed, as
    the whole ontology must be read into main memory.
    Further, the multi-user support and transactions
    are typically not present, so the whole
    infrastructure realizing these requirements must
    be created from scratch but my project is web
    based and it is able support multi-user
    transactions.

40
Conclusion
  • The Music Ontology is an application of the
    Ontology Web Language (OWL) because the subject
    area are music artists, albums and tracks etc
    -- has so many competing requirements that a
    standalone format would not capture them or would
    lead to trying to describe these requirements in
    a number of incompatible formats. By using OWL,
    the Music Ontology gains a powerful extensibility
    mechanism, allowing Music-Ontology-based
    descriptions to be mixed with claims made in any
    other OWL vocabulary.
  • OWL provides the Music Ontology with a way to mix
    together different descriptive vocabularies in a
    consistent way. Vocabularies can be created by
    different communities and groups as appropriate
    and mixed together as required, without needing
    any centralized agreement.
  • In summary then, OWL is self-documenting in ways
    which enable the creation and combination of
    vocabularies in a devolved manner. This is
    particularly important for an ontology which
    describes communities, since online communities
    connect into many other domains of interest,
    which it would be impossible (as well as
    suboptimal) for a single group to describe
    adequately in non-geological time.

41
References
  • 1- http//purl.org/
  • 2- Multimedia Content and the Semantic Web
    METHODS, STANDARDS AND TOOLS Edited by
    Giorgos Stamou and Stefanos Kollias Both of
    National Technical University of Athens, Greece.
    John Wiley Sons Ltd.
  • 3- T. Berners-Lee, J. Hendler, O. Lassila, The
    Semantic Web. Scientific American, 284(5),
    3443, 2001.
  • 4- O. Lassila, R.R. Swick, Resource Description
    Framework (RDF) Model and Syntax Specification,
    http//www.w3.org/TR/REC-rdf-syntax/.
  • 5- D. Brickley, R.V. Guha, RDF Vocabulary
    Description Language 1.0 RDF Schema,
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  • 8- P.F. Patel-Schneider, P. Hayes, I.
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  • 9- C. Davis, S. Jajodia, P. Ng, R. Yeh (eds),
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42
References (Cont1)
  • 11- A. Evans, A. Clark, Foundations of the
    Unified Modeling Language. Springer-Verlag,
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  • 12- http//pingthesemanticweb.com/ontology/mo/s
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  • 14- http//www.w3.org/2001/sw/, no pagination,
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  • 15- Tim Berners-Lee, James Hendler, and Ora
    Lassila. The semantic web. Scientific American,
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  • 16- Ubbo Visser Intelligent Information
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  • 17- Semantic Web Technologies Trends and
    Research in Ontology-based Systems John Davies
    BT, UK Rudi Studer University of Karlsruhe,
    Germany Paul Warren BT, UK John Wiley Sons
    Ltd.
  • 18- http//www.w3.org/2004/OWL/
  • 19- http//www.w3.org/RDF/
  • 20- The Semantic Web A Guide to the Future of
    XML, Web Services, and Knowledge Management
    Michael C. Daconta Leo J. Obrst Kevin T. Smith
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  • 22- Protégé overview, URL http//protege.stanfo
    rd.edu, last visited June 2006

43
References (Cont2)
  • 23- N. F. Noy, M. Sintek, S. Decker, M.
    Crubezy, R. W. Fergerson, M. A. Musen.
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    Environment for Knowledge-Based Systems
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  • 25- Erhan Gayde Thesis Eastern Mediterranean
    University September 2006, Gazimagusa, North
    Cyprus
  • 26- http//www.Borlan.com/
  • 27- Jena A Semantic Web Framework for Java,
    URL
  • http//jena.sourceforge.net/.
  • 28- HP Labs Semantic Web Research, URL
  • http//www.hpl.hp.com/semweb/.
  • 29- http//jena.sourceforge.net/tutorial/RDQL/
  • 30- Borland JBuilder 2006 Documentation Files.
  • 31- http//algernon-j.sourceforge.net/
  • 32- http//www.hewettresearch.com/mikehewett.htm
    l
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  • 35- Microsoft SQL Server 2005 Documentation

44
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